Object based image processing

1. A method comprising:

receiving, at an image processing device, image data corresponding to an image;

determining object quality values based on a portion of the image data, the portion corresponding to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object; and

generating a notification indicating that the image data has been altered in response to a result of a comparison of the object quality values to the object category metrics, the result indicating alteration of the portion of the image data.

2. The method of claim 1 , further comprising:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object category metrics, wherein generating the notification is further responsive to a second result of the second comparison indicating alteration of the second portion of the image data.

3. The method of claim 1 , further comprising:

detecting the object represented in the image based on the image data;

selecting the portion of the image; and

determining the object category corresponding to the object.

4. The method of claim 3 , further comprising comparing the object quality values to basis representations in an object category repository.

5. The method of claim 1 , wherein the result indicates the alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

6. The method of claim 1 , wherein the object comprises a representation of a portion of a person.

7. The method of claim 6 , wherein the portion of the person comprises a face of the person or hair of the person.

8. The method of claim 1 , further comprising modifying an image processing parameter of an image processing device based on the result, the image processing parameters comprising an image resolution parameter, a frame rate parameter, an encoding parameter, a bandwidth parameter, a bitrate parameter, or an image capture device mode parameter.

9. The method of claim 1 , further comprising:

modifying values of the image data corresponding to the object based on the comparison to generate modified image data; and

initiating output of a second image based on the modified image data.

10. The method of claim 1 , wherein the image comprises a frame of a video stream.

11. A system comprising:

a processor; and

a memory accessible to the processor, the memory comprising instructions that, when executed by the processor, cause the processor to execute operations including:

receiving image data corresponding to an image;

determining object quality values based on a portion of the image data, wherein the portion corresponds to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object;

performing a comparison of the object quality values to the object category metrics; and

generating a notification indicating that the image data has been altered based on a result of the comparison.

12. The system of claim 11 , wherein the processer and the memory are included in a mobile device.

13. The system of claim 11 wherein the processor and the memory are included in a media device.

14. The system of claim 11 , wherein the result of the comparison indicates alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

15. The system of claim 11 , wherein the operations further include:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object quality category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object quality category metrics, wherein generating the notification is further responsive to a second result of the second comparison indicating alteration of the second portion of the image data.

16. A computer-readable storage device comprising instructions executable by a processor to perform operations comprising:

receiving image data corresponding to an image;

selecting a portion of the image data corresponding to an object represented in the image;

determining object quality values based on a portion of the image data, wherein the portion corresponds to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object; and

generating a notification indicating that the image data has been altered based on a result of a comparison of the object quality values to the object category metrics.

17. The computer-readable storage device of claim 16 , wherein the operations further include:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object category metrics.

18. The computer-readable storage device of claim 16 , wherein the operations further include performing the comparison, wherein the comparison indicates alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

19. The computer-readable storage device of claim 16 , wherein the object category metrics include a sharpness metric, a blurriness metric, a low-lighting metric, a texture metric, a color metric, or a combination thereof.

20. The computer-readable storage device of claim 16 , wherein the operations further comprise:

detecting the object represented in the image based on the image data;

selecting the portion of the image based on the object; and

determining the object category corresponding to the object.